The decline in agricultural labor force not only makes it difficult to operate the agricultural machinery itself, but also leads to a tendency to avoid more dangerous work when it is involved, leading to a decrease in agricultural productivity. In particular, in the case of agricultural fields such as orchards, which target field crops, there are many restrictions on the development of unmanned technologies to reinforce the labor force. In the case of orchards, the most common work is to use a control device to spray pesticides. The control method of the existing batch spraying method causes excessive use of pesticides and scattering problems to neighboring farms, and in particular, farmers in the field are damaged by exposure. For this study, using a LiDAR sensor that has strong straightness and can accurately recognize the location of an object, it recognizes the shape of a fruit tree based on 3D location data, and applies down sampling and threshold processing techniques. In addition, it has been prepared so that hardware can be easily configured by simply installing an injection device, a controller, and a sensor in the existing commercial control unit. By recognizing the shape of the fruit tree and spraying pesticides only where necessary, a control algorithm was developed to reduce the use of pesticides and efficiently control work, and the effects were compared and analyzed through the paper cut.